Experimental study of extracting artificial boundary condition frequencies for dynamic model updating

Chuanchuan Hou, Lei Mao, Yong Lu

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

In the field of dynamic measurement and structural damage identification, it is generally known that modal frequencies may be measured with higher accuracy than mode shapes. However, the number of natural frequencies within a measurable range is limited. Accessing additional forms of modal frequencies is thus desirable. The present study is concerned about the extraction of artificial boundary condition (ABC) frequencies from modal testing. The ABC frequencies correspond to the natural frequencies of the structure with a perturbed boundary condition, but they can be extracted from processing the frequency response functions (FRF) measured in a specific configuration from the structure in its existing state without the need of actually altering the physical support condition. This paper presents a comprehensive experimental investigation into the measurability of the ABC frequencies from physical experiments. It covers the testing procedure through modal testing, the data processing and data analysis requirements, and the FRF matrix operations leading to the extraction of the ABC frequencies. Specific sources of measurement errors and their effects on the accuracy of the extracted ABC frequencies are scrutinised. The extracted ABC frequencies are subsequently applied in the damage identification in beams by means of finite element model updating. Results demonstrate that it is possible to extract the first few ABC frequencies from the modal testing for a variety of artificial boundary conditions incorporating one or two virtual pin supports, and the inclusion of ABC frequencies enables the identification of structural damages without the need to involve the mode shape information.
Original languageEnglish
Number of pages15
JournalSmart Structures and Systems
Issue number2
Publication statusPublished - 31 Aug 2017


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